Smart Grid Energy Management: The Role of AI in Efficiency and Stability

Abstract

Applying a smart grid energy management system can control and analyze the properties of
demand, and supply devices in this regard integrating artificial intelligence AI into Smart Energy
Meter generation. In the following sections, this paper attempts to investigate different AI
applications in smart grid operations and their effects on improving grid performance as well as
discusses challenges along with opportunities arising from the mainstreaming of AI technologies
for energy sector. This research work focuses on the Smart grid demand, load balancing, and
fault detection using AI-driven technologies. Research design: A smart grid system connected
with real-time sensors and equipment such as the smart meter records data in quasi-real time. In
this paper, a comparative study is conducted to assess the performance of various AI algorithms
for Load Balancing Enhancement and Energy Loss Minimization in Microgrids based on which
an optimized operational cost model was developed. Results from this study prove what AI can
achieve in transforming the efficiency and reliability of smart grid systems with noticeable
enhancement in energy conservation and operational stability. To confirm, the findings have
justified AI as a helpful tool and provided useful information for moving toward even more
innovative energy management technology.